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modelling analyses, including differential gene expression analysis, microbiome diversity analyses, host–microbiome association testing, metagenome-wide association analyses (mGWAS), hierarchical Bayesian
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processes of the study systems of our collaborators. Core components of the research involve, among others, Bayesian hierarchical modelling, shrinkage methods, machine learning (ML) or dimension reduction
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the objectives of this PhD project. The person appointed will be affiliated with the research group Renewable Energy and Advanced Construction Technologies Laboratory (REACT-Lab). Duties Complete the doctoral
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synthesis of timed and probabilistic behavioral models for model checking, performance evaluation, and optimization. The overall objective is to establish formal foundations that bridge static engineering
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research, and sustainable societal development. Research objectives The postdoctoral project addresses a fundamental scientific challenge: how heterogeneous research data, models, and knowledge